DevOps Manager - Waterbury

Only for registered members Waterbury, United States

3 weeks ago

Default job background
Full time $110,000 - $125,000 (USD)
Job summary: The role involves working with Webster's data systems and tools to design, implement, configure, maintain hardware, software, and data pipelines for Finance Analytics (FAST). Ability to anticipate and resolve challenges, generate clear action plans and communicate results. Primary responsibilities: Develop expert knowledge and experience with Webster's data systems and tools. Designing building maintaining infrastructure Execute CECL Quarterly Production Process Annual Refresh Build automate monitor statistical machine learning model workflows from development production Analyze organize system datasets derive actionable insights create efficient low maintenance pipelines Develop data workflows support ingestion wrangling transformation reporting dashboarding Build manage CI CD pipelines ensure reliable secure repeatable deployments Collaborate teams analyze requirements propose infrastructure pipeline solutions Use Snowflake access processing creating robust data pipelines integrations Manage science notebooks production environments e.g SageMaker Studio JupyterHub Use Git version control workflow management codebases projects Collaborate cross functional teams understand requirements implement effective solutions Key Skills Experience 5+ years experience working in engineering DevOps specializing AI Machine Learning deployment Experience complex structures RDMS Oracle SQL Programming languages packages Python Keras Tensorflow PyTorch Pandas Scikit learn Jupyter etc Proficient Python SAS Programming Language Traditional ML deep techniques CNN RNN LSTMs GANs model tuning validation algorithms Familiarity commercial consumer banking products operations processes risk finance background experience Cloud services computing platforms AWS SageMaker S3 EC2 Redshift Athena Glue Lambda equivalent Azure/GCP Reporting Dashboarding tools Tableau Qlik Sense Extensive engineering design coding testing patterns large-scale infrastructures DevOps leveraging CI CD services Airflow GitLab Terraform Jenkins Data Science project implementation Documenting processes scripts memos clearly internal audits Strong analytical problem-solving skills collaborative team environment Excellent communication convey complex concepts non-technical stakeholders Ingenuity analytical thinking resourceful persistent pragmatic motivated socially intelligent Time management prioritize multiple tasks Desired Attributes Familiarity Docker Kubernetes containerized deployments Experience Terraform AWS CDK infrastructure-code tools Knowledge ETL ELT orchestration monitoring logging best practices cloud-based environments Familiarity programming language Confluence documentation collaboration Knowledge Tidal workflow automation scheduling tools Developing constructive relationships wide range stakeholders Machine Learning Deep Learning models independently gather research think “box” suggestions improve process Education Bachelor Master PhD computer science data science STEM fields physics math engineering other degrees strong computer science background acceptable
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